Scientists have invented a headband they claim can detect signs of Alzheimer’s disease while the wearer sleeps.
The device – dubbed ‘a Fitbit for the brain’ – contains tiny sensors that monitor brainwaves.
It is programmed to pick up on changes to the part of the brain responsible for memory reactivation, which is determined by different proteins.
Researchers had more than 200 patients in their 70s wear the headband six nights a week over two years in the first-of-its-kind study that could lead to inexpensive wearable EEG devices that monitor brain health, detect preclinical AD, and track treatment response.
The device, fitted with electroencephalography (EEG), monitors brain wave patterns related to memory reactivation
Alzheimer’s is a progressive, degenerative disease of the brain in which the build-up of abnormal proteins causes nerve cells to die.
This disrupts the transmitters that carry messages and causes the brain to shrink.
More than 5 million people suffer from the disease in the US, the sixth leading cause of death nationwide.
The headband was invented by scientists from the University of Colorado Anschutz Medical Campus and Washington University in St. Louis, who discovered a method to evaluate brain activity during sleep linked to the initial phases of Alzheimer’s disease, often manifesting long before dementia symptoms appear.
Brice McConnell, with the University of Colorado School of Medicine and study senior author, said: ‘This digital biomarker essentially enables any simple EEG headband device to be used as a fitness tracker for brain health.
Researchers analyzed data from 205 aging adults, identifying measurable problems with memory reactivation associated with levels of proteins such as amyloid and tau that build up in Alzheimer’s Disease. Pictured is the lead scientist, Brice McConnell
‘Demonstrating how we can assess digital biomarkers for early indications of disease using accessible and scalable headband devices in a home setting is a huge advancement in catching and mitigating Alzheimer’s disease at the earliest stages.’
All participants were either cognitively unimpaired very mildly cognitively impaired, except one participant who was mildly cognitively impaired.
The team hypothesized that the headband could find potential biomarker properties linked to memory reactivation during sleep.
These biomarkers include theta bursts (TB) that improve depression, sleep spindles (SP) associated with non-rapid eye movement, and slow waves (SW), the deepest sleep level lasting up to 40 minutes during each period.
Researchers believe changes in the ‘coupling’ of these events may indicate early Alzheimer’s disease (AD) pathogenesis.’
The team used the headband to map SW-TB and SW-SP neural circuit coupling precision to amyloid positivity, cognitive impairment and cerebrospinal fluid (shock absorber for the brain) Alzheimer’s biomarkers.
The headband sits on the head comfortably, allowing wearers to sleep with it
Previous research has shown that Alzheimer’s disease is caused by the accumulation of amyloid beta protein in the brain, leading to neuronal toxicity in the central nervous system.
Following the data collection, researchers determined that cognitive impairment correlated with lower TB concentration in SW-TB coupling.
And those cognitively unimpaired demonstrated lower precision in SW-TB and SW-SP coupling.
‘What we found is these abnormal levels of proteins are related to sleep memory reactivations, which we could identify in people’s brainwave patterns before they experienced any symptoms,’ said McConnell.
‘Identifying these early biomarkers for Alzheimer’s disease in asymptomatic adults can help patients develop preventative or mitigation strategies before the disease advances.’
Researchers also believe this is an exciting step towards using wearables as digital biomarkers for disease detection.
‘We are just scratching the surface with this work, paving the way for affordable and easy-to-use devices to monitor brain health,’ says McConnell.
‘This is proof of principle that brain waves during sleep can be turned into a digital biomarker, and our next steps involve perfecting the process.’
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